myusuf3

To remove a submodule you need to:

• Delete the relevant section from the .gitmodules file.
• Stage the .gitmodules changes git add .gitmodules
• Delete the relevant section from .git/config.
• Run git rm --cached path_to_submodule (no trailing slash).
• Run rm -rf .git/modules/path_to_submodule (no trailing slash).
• Commit git commit -m "Removed submodule "
• Delete the now untracked submodule files rm -rf path_to_submodule

swlaschin

(*
CapabilityBasedSecurity_ConfigExample.fsx

An example of a simple capability-based design.

Related blog post: http://fsharpforfunandprofit.com/posts/capability-based-security/
*)
 
/// Configuration system
module Config =

mastoj

module Person = 
    open System
    type PersonState = private { id: Guid; name: string; age: int}
    let createPerson id name age = {id = id; name = name; age = age}
    let changeName name personState = {personState with name = name}
    let changeAge age personState = 
        // some crazy business rule involving age
        {personState with age = age}

module SomeOtherModule = 

ipropper

//CLIENT
// this method is quick and dirty, but should get the service up and running

import javax.net.SocketFactory;
import javax.net.ssl.SSLSocket;
import javax.net.ssl.SSLSocketFactory;
import java.io.IOException;
import java.io.OutputStreamWriter;

tobilg

Custom S3 endpoints with Spark

To be able to use custom endpoints with the latest Spark distribution, one needs to add an external package (hadoop-aws). Then, custum endpoints can be configured according to docs.

Use the hadoop-aws package

bin/spark-shell --packages org.apache.hadoop:hadoop-aws:2.7.2

SparkContext configuration

bastman

Docker - How to cleanup (unused) resources

Once in a while, you may need to cleanup resources (containers, volumes, images, networks) ...

delete volumes

// see: https://github.com/chadoe/docker-cleanup-volumes

$ docker volume rm $(docker volume ls -qf dangling=true)

$ docker volume ls -qf dangling=true | xargs -r docker volume rm

dcode

GitHub Flavored Asciidoc (GFA)

walm

package main

import (
	"fmt"
	"log"
	"strconv"

	"github.com/miekg/dns"
)

jpallari

Enforcing invariants in Scala datatypes

Scala provides many tools to help us build programs with less runtime errors. Instead of relying on nulls, the recommended practice is to use the Option type. Instead of throwing exceptions, Try and Either types are used for representing potential error scenarios. What’s common with these features is that they’re used for capturing runtime features in the type system, thus lifting the runtime scenario handling to the compilation phase: your program doesn’t compile until you’ve explicitly handled nulls, exceptions, and other runtime features in your code.

In his “Strategic Scala Style” blog post series,

yoyama

/**
  * Generate Case class from DataFrame.schema
  *
  *  val df:DataFrame = ...
  *
  *  val s2cc = new Schema2CaseClass
  *  import s2cc.implicit._
  *
  *  println(s2cc.schemaToCaseClass(df.schema, "MyClass"))
  *